NBLDA - Negative Binomial Linear Discriminant Analysis
We proposed a package for the classification task which
uses Negative Binomial distribution within Linear Discriminant
Analysis (NBLDA). It is an extension of the 'PoiClaClu' package
to Negative Binomial distribution. The classification
algorithms are based on the papers Dong et al. (2016, ISSN:
1471-2105) and Witten, DM (2011, ISSN: 1932-6157) for NBLDA and
PLDA, respectively. Although PLDA is a sparse algorithm and can
be used for variable selection, the algorithm proposed by Dong
et al. is not sparse. Therefore, it uses all variables in the
classifier. Here, we extend Dong et al.'s algorithm to the
sparse case by shrinking overdispersion towards 0 (Yu et al.,
2013, ISSN: 1367-4803) and offset parameter towards 1 (as
proposed by Witten DM, 2011). We support only the
classification task with this version.